Method and device for positioning vehicle, device, and computer readable storage medium

ABSTRACT

Embodiments of the present disclosure provide a method and a device for positioning a vehicle, a device, and a computer readable storage medium. The method includes: determining first edge information of a vehicle from an image related to the vehicle and acquired by a sensing device; determining a contour model corresponding to the vehicle; determining second edge information that matches the first edge information from an edge information set associated with the contour model, in which each edge information in the edge information set corresponds to a position of the contour model relative to the sensing device; and determining a position of the vehicle relative to the sensing device based on a position corresponding to the second edge information.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to and benefits of Chinese PatentApplication No. 201811151044.9, filed with the National IntellectualProperty Administration of P. R. China on Sep. 29, 2018, the entirecontents of which are incorporated herein by reference.

TECHNICAL FIELD

The present disclosure relates to the field of intelligent driving, andmore particularly, to a method and a device for positioning a vehicle, adevice, and a computer readable storage medium.

BACKGROUND

In recent years, autonomous driving and assisted driving have developedrapidly. In the field of autonomous driving and assisted driving,high-precision positioning of the vehicle is important. In practicalapplications, global satellite navigation system (GNSS) positioning mayhave errors of up to 10 meters or more. Some autonomous driving andassisted driving vehicles can achieve higher precision positioning bycombining high-precision inertial navigation system (INS) and GNSS, orby combining high-precision maps and laser radars. However, such manneris costly and can be affected by external environments. Therefore, itbecomes a focus of attention to achieve high-precision positioning ofthe vehicle.

SUMMARY

Embodiments of the present disclosure provide a solution for controllingautonomous driving of a vehicle.

The present disclosure provides a method for positioning a vehicle. Themethod includes: determining first edge information of a vehicle from animage related to the vehicle and acquired by a sensing device;determining a contour model corresponding to the vehicle; determiningsecond edge information that matches the first edge information from anedge information set associated with the contour model, in which eachedge information in the edge information set corresponds to a positionof the contour model relative to the sensing device; and determining aposition of the vehicle relative to the sensing device based on aposition corresponding to the second edge information.

The present disclosure provides a device including one or moreprocessors, and a storage device. The storage device is configured tostore one or more programs. When the one or more programs are executedby the one or more processors, the electronic device is caused toimplement the method according to embodiments of the present disclosure.

The present disclosure provides a computer readable storage mediumhaving a computer program stored thereon. When the computer program isexecuted by a processor, the method according to embodiments of thepresent disclosure is caused to be implemented.

It is to be understood that, the content described in the summary is notintended to limit the key or important features of the presentdisclosure, or the scope of the present disclosure. Other features ofthe present disclosure will be readily understood by the followingdescription.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other aspects and advantages of embodiments of the presentdisclosure will become apparent and more readily appreciated from thefollowing descriptions made with reference to the drawings. In thedrawings, the same or similar reference numerals indicate the same orsimilar elements, in which:

FIG. 1 is a schematic diagram of an exemplary environment forimplementing an embodiment of the present disclosure.

FIG. 2 is a flow chart of a method for positioning a vehicle accordingto an embodiment of the present disclosure.

FIG. 3A is a schematic diagram of a vehicle to be positioned accordingto an embodiment of the present disclosure.

FIG. 3B is a schematic diagram of first edge information of a vehicleaccording to an embodiment of the present disclosure.

FIG. 4 is a schematic diagram of a contour model of a vehicle accordingto an embodiment of the present disclosure.

FIG. 5 is a schematic diagram of second edge information according to anembodiment of the present disclosure.

FIG. 6 is a block diagram of a device for positioning a vehicleaccording to an embodiment of the present disclosure.

FIG. 7 is a block diagram of a computing device capable of implementingan embodiment of the present disclosure.

DETAILED DESCRIPTION

The present disclosure will be described in detail below with referenceto the accompanying drawings. Although certain embodiments of thepresent disclosure are shown in the drawings, it should be understoodthat, the present disclosure may be implemented in various forms, andshould not be construed as being limited to the embodiments set forthherein. Instead, the embodiments are provided to provide a more completeand clear understanding of the present disclosure. It should beunderstood that, the drawings and embodiments of the present disclosureare for illustrative purpose only and are not intended to limit thescope of the present disclosure.

In the description of embodiments of the present disclosure, the term“include” and the like should be understood as open inclusion, i.e.,“including but not limited to”. The term “based on” should be understoodas “at least partially based on”. The term “one embodiment” or “theembodiment” should be understood as “at least one embodiment”. The terms“first”, “second” and the like may refer to different or identicalobjects. Other explicit and implicit definitions may also be includedbelow.

As mentioned above, the high-precision positioning of the vehicle is thebasis for achieving autonomous driving. In positioning technology in therelated art, GNSS positioning cannot meet the precision requirement ofautonomous driving, and positioning based on the high-precision maprequires the vehicle to be equipped with high-cost laser radar, and themap suppliers are also required to maintain the high precision map toensure the accuracy of the high-precision map.

In recent years, with the advancement of communication technology,vehicle-to-everything (V2X) technology has been developed rapidly. Whena vehicle determines its position, it can improve the positioningaccuracy by using positioning information determined by a roadsidedevice or positioning information determined by other vehicles. Forexample, the vehicle on the road may be positioned based on the image ofthe vehicle taken by a roadside camera. In the related art, the roadsidecamera may extract contour information of the vehicle from a video imageby image processing algorithms such as edge extraction, and estimate thegeographic position of the vehicle based on the position of the contourinformation in the image and the calibration information of the roadsidecamera. Such positioning manner tends to have large errors, and cannotachieve the accuracy requirement of autonomous driving.

Embodiments of the present disclosure provide a solution for positioninga vehicle using a sensing device. In the solution, the sensing devicemay acquire an image related to the vehicle, and determine edgeinformation of the vehicle from the image. The sensing device may alsoacquire a contour model corresponding to a target vehicle, and determineedge information that matches the first edge information from an edgeinformation set associated with the contour model. The matched edgeinformation corresponds to the position of the contour model relative tothe sensing device. Based on the position of the contour model, thesensing device can determine the geographic position of the vehicle. Byadjusting the coordinate and angle of the pre-stored vehicle contourmodel relative to the sensing device to match vehicle edge informationin the video image, the sensing device can accurately determine theposition and angle of the vehicle.

Embodiments of the present disclosure will be described in detail belowwith reference to the drawings.

FIG. 1 is a schematic diagram of an exemplary environment 100 forimplementing an embodiment of the present disclosure. As illustrated inFIG. 1, the exemplary environment 100 may include a road 102, one ormore sensing devices 105-1, 105-2, 105-3 and 105-4, and one or morevehicles 110-1, 110-2. For convenience of description, the plurality ofsensing devices 105-1, 105-2, 105-3, and 105-4 are collectively referredto as the sensing device 105, and the plurality of vehicles 110-1, 110-2are collectively referred to as the vehicle 110. It should be understoodthat, the illustrated facilities and objects are for illustrativepurposes only, and objects presented in different traffic environmentsmay vary depending on actual situations. The scope of the presentdisclosure is not limited in this respect.

In FIG. 1, one or more vehicles 110-1, 110-2 are traveling on the road102. Vehicle 110 may be any type of vehicle that can carry personsand/or objects, and be moved by a power system such as an engine,including but not limited to cars, trucks, buses, electric vehicles,motorcycles, recreational vehicles, trains, etc. The one or more ofvehicles 110 in the environment 100 may be unmanned vehicles, which havethe autonomous driving capability. Certainly, the other or some of thevehicles 110 in the environment 100 may not have the autonomous drivingcapability.

In an embodiment, the sensing device 105 (e.g., 105-1 and 105-2) in theenvironment 100 may be a roadside device that is independent of thevehicle 110 for monitoring the condition of the environment 100, so asto acquire perceptive information related to the environment 100. Insome embodiments, the sensing device 105 (e.g., 105-1) may be disposedabove the road 102. In some embodiments, the sensing device 105 (e.g.,105-2) may be disposed on both sides of the road 102. In someembodiments, the sensing device 105 (e.g., 105-3 and 105-4) may bemounted on the vehicle 110. In an embodiment, the sensing device 105 mayinclude an image sensor, to acquire image information of the road 102and the vehicle 110 in the environment 100. In some embodiments, thesensing device may also include one or more other types of sensors, suchas a laser radar, or a millimeter wave radar.

The process of positioning a vehicle according to an embodiment of thepresent disclosure will be described below with reference to FIG. 2 toFIG. 5. For convenience of description, the process of positioning thevehicle 110 using the sensing device 105 may be described with aroadside device as an example. It should be understood that, based onthe solution of the present disclosure, it may also be possible tolocate another vehicle using the sensing device (e.g. 105-3 and 105-4)mounted on the vehicle. FIG. 2 is a flow chart of a method 200 forpositioning a vehicle according to an embodiment of the presentdisclosure. The method 200 may be performed by the sensing device 105shown in FIG. 1.

At block 202, the sensing device 105 determines edge information(hereinafter referred to as first edge information for convenience ofdescription) of a vehicle from an image related to the vehicle.

In some embodiments, when the vehicle 110 passes through the area nearthe sensing device 105, the sensing device 105 may acquire the imagerelated to the vehicle 110. For example, FIG. 3A illustrates anexemplary image 300 of a vehicle 110 to be positioned according to anembodiment of the present disclosure.

In some embodiments, the sensing device 105 may determine the first edgeinformation indicating the edge of the vehicle 110 by using edgeextraction algorithms in the related art, such as the Canny edgedetection algorithm, the machine learning and target segmentationalgorithm, etc. It should be understood that, the edge extractionalgorithms described above are merely illustrative, and other suitableedge extraction algorithms may be employed to determine the edgeinformation of the vehicle 110.

FIG. 3B is a schematic diagram of edge information 300′ of the vehicle110 to be positioned according to an embodiment of the presentdisclosure. In some embodiments, the sensing device 105 may determine atleast one component of the vehicle 110 from the image 300 by utilizingapproaches such as machine learning. Examples of the component mayinclude, but are not limited to, a window, a sunroof, a headlight, anactive grille shutter, etc. The sensing device 105 may extract the edgeof each of the at least one component in the image 300 by the edgeextraction algorithm described above. FIG. 3B illustrates the body edge302, the sunroof edge 304, the front window edge 306, the headlight edge308 and the active grille shutter edge 310 of the vehicle 110 extractedfrom the image 300. It should be understood that, these components aremerely illustrative, and the sensing device 105 may also extract edgeinformation of other components of the vehicle 110 in the image 300.

At block 204, the sensing device 105 determines a contour modelcorresponding to a vehicle.

In some embodiments, the sensing device 105 may determine identificationinformation of the vehicle 110 from the image 300. In some embodiments,the identification information may include registration plateinformation of the vehicle 110. For example, the sensing device 105 maydetermine the registration plate information of the vehicle 110 from theimage 300 by an image recognition algorithm. It should be understoodthat, any suitable image recognition algorithm may be employed todetermine registration plate information of the vehicle 110, which isnot described in detail herein.

In some embodiments, the identification information may include otherinformation related to the vehicle 110, such as barcode information andradio frequency identification (RFID) information. For example, thebarcode information may be printed or affixed to the outer casing of thevehicle 110, or the vehicle 110 may be fitted with an RFID tag. Byidentifying the barcode information or reading the RFID information, thesensing device 105 can determine identification information of thevehicle 110, such as registration plate of the vehicle 110 or the modelof the vehicle 110, etc.

In some embodiments, the sensing device 105 may determine the contourmodel corresponding to the vehicle 110 from a preset contour model setbased on the identification information. The sensing device 105 maystore a preset contour model set, which may include contour modelscorresponding to different registration plate information. The sensingdevice 105 can determine the contour model corresponding to the vehicle110 based on the registration plate information of the vehicle 110.

In some embodiments, the contour model set may include contour modelscorresponding to different vehicle models. The sensing device 105 maydetermine the model of the vehicle 110 based on the registration plateinformation of the vehicle 110 or information such as barcode/RFID, anddetermine the contour model corresponding to the vehicle 110 from thecontour model set based on the model of the vehicle 110.

In some embodiments, the contour model set may be stored at a computingdevice separate from the sensing device 105. The sensing device 105 maysend identification information of the vehicle 110 or the model of thevehicle 110 determined based on the identification information to thecomputing device, thereby requesting the contour model corresponding tothe vehicle 110 from a server. After the request is received, thecomputing device may determine the contour model corresponding to thevehicle 110 from the contour model set based on the identificationinformation or the model of the vehicle 110, and send the contour modelto the sensing device 105.

FIG. 4 is a schematic diagram of a contour model 400 of a vehicleaccording to an embodiment of the present disclosure. In the exampleshown in FIG. 4, the sensing device 105 determines a contour model 400corresponding to the vehicle 110 from the contour model set. In someembodiments, the contour model 400 may include, for example, contourinformation as well as physical size information corresponding to thevehicle 110. In some embodiments, the contour model 400 may includecontour information associated with different components of the vehicle110. For example, as shown in FIG. 4, the contour model 400 may includea rear window contour 402, a sunroof contour 404, a front window contour406, a headlight contour 408, and an active grille shutter contour 410.In some embodiments, the contour model 400 may be converted into aplurality of lines in a coordinate system originating from the contourmodel (hereinafter referred to as a first coordinate system forconvenience of description), and these lines may be represented asequations in the first coordinate system.

At block 206, the sensing device 105 determines edge information(hereinafter referred to as second edge information for convenience ofdescription) that matches the first edge information from an edgeinformation set associated with the contour model. Each edge informationin the edge information set corresponds to a position of the contourmodel relative to the sensing device 105.

In some embodiments, the sensing device 105 may set the initial positionof the contour model 400 relative to the sensing device 105 toX^(T)=(x,y,z,α,β,γ), where (x,y,z) denotes the coordinate of the centerof the contour model 400 at a coordinate system originating from thesensing device 105 (hereinafter referred to as a second coordinatesystem for convenience of description), (α,β,γ) denotes the Euler angleof the first coordinate relative to the second coordinate system, whichembodies pitch, roll and yaw information of the contour model 400relative to the sensing device 105. In some embodiments, the initialposition of the contour model 300 relative to the sensing device 105 maybe determined based on the center of the vehicle 110 in the image 300.For example, in some embodiments, the sensing device 105 may convert thetwo-dimensional (2D) coordinates of the center of the vehicle 110 in theimage 300 to a position in the second coordinate system according to itscalibration information, and take the position as the initial positionof the contour model 400. It should be understood that, the conversionof the 2D coordinates of the center of the vehicle 110 in the image 300to the position in the second coordinate system may be performed bywell-known coordinate conversion manners in the related art, which willnot be described in detail herein.

In some embodiments, based on the determined position of the contourmodel 400 relative to the sensing device 105 and its calibrationinformation, the sensing device 105 may determine edge informationcorresponding to the contour model 400 in a 2D coordinate system of theimage 300 (hereinafter referred to as a third coordinate system forconvenience of description). For example, FIG. 5 is a schematic diagram500 of second edge information according to an embodiment of the presentdisclosure. As shown in FIG. 5, taking the front window contour 406 asan example, the sensing device 105 can determine a contour line 502corresponding to the front window contour 406 in the third coordinatesystem based on the position of the contour model 400. In detail, thesensing device 105 may also obtain an equation of each of the one ormore line segments constituting the contour line 502 in the thirdcoordinate system.

In some embodiments, the sensing device 105 may determine a distancebetween the edge (hereinafter referred to as a first edge forconvenience of description) indicated by the first edge information andthe edge indicated by the edge information projected by the contourmodel 400 projected in the third coordinate system. As shown in FIG. 5,taking the front window contour 406 as an example, the sensing device105 may determine the distance between the front window edge 306 and thecontour line 502 in the coordinate system of the image 300. In someembodiments, the sensing device 105 determines a plurality of points onthe first edge. For example, the sensing device 105 may sample aplurality of points 504, 506 from the front window edge 306, andcalculate a distance between each of the plurality of points 504, 506and the contour line 502, respectively.

In some embodiments, the sensing device 105 may determine a line segmentthat is closest to the point 504 or 506, and calculate the shortestdistance from the point 504 or 506 to the line segment. Taking the point504 in FIG. 5 as an example, the coordinates of the point 504 in thethird coordinate system may be represented as (u₀, v₀), and the linesegment that is closest to the point 504 is line segment 580. Theequation of the line segment 508 in the third coordinate system may be,for example, expressed as au+bv+1=0, where u and v are coordinate axesof the third coordinate system, and a and b are coefficients of thelinear equation of the line segment 508 in the third coordinate system.The distance D from the point 504 to the line segment 508 may beexpressed as:

$\begin{matrix}{D = \frac{{{a\; u_{0}} + {bv}_{0} + 1}}{\sqrt{a^{2} + b^{2}}}} & (1)\end{matrix}$

Since the position of the contour model 400 of the vehicle 110 in thefirst coordinate system is known, the coefficients a and b of the linearequation may be expressed as a function of the positionX^(T)=(x,y,z,α,β,γ) of the contour model 400 relative to the sensingdevice 105, for example, a and b may be expressed as:

a=f ₁(x,y,z,α,β,γ)  (2)

b=f ₂(x,y,z,α,β,γ)  (3)

By substituting the function (2) of a and function (3) of b intoequation (1), it can be obtained that D=F(x,y,z,α,β,γ). In the samemanner, the distance from the point 506 to the contour line 502 may bedetermined as the distance from the point 506 to the nearest linesegment 510, which may also be represented as a function of positionX^(T)=(x,y,z,α,β,γ).

In some embodiments, the sensing device 105 may determine the sum ofdistances between the plurality of points on the edge indicated by theedge information and the contour line. Specifically, in the example ofFIG. 5, in the case where only the front window edge 306 is considered,the distance between the front window edge 306 and the contour line 502at the coordinate system of the image 300 may be represented as the sumE of the distances between the plurality of points 504 and 506 and thecontour line 502. Thus, E can be expressed as a function of the positionof the contour model 400 in the second coordinate system:

E=ΣF _(i)(x,y,z,α,β,γ)=g(x,y,z,α,β,γ)

where i denotes the number of the plurality of points. It should beunderstood that, E may include the sum of the distances of a pluralityof points on the edge (e.g., the body edge 302, the sunroof edge 304,the headlight edge 308, and the active grille shutter edge 310)corresponding to the other components to the corresponding contourlines.

It should be understood that, the smaller the sum E is, the closer thecontour model 400 will be to the true position of the vehicle 110.Therefore, the sensing device 105 needs to make the second edgeindicated by the second edge information corresponding to the contourmodel coincide with the first edge indicated by the first edgeinformation 300′ in the image 300 as much as possible.

In some embodiments, the sensing device 105 may perform iterativeadjustment based on the initial position X^(T)=(x,y,z,α,β,γ) of thecenter of the contour model 400 in the second coordinate system.Specifically, the sensing device 105 may compare the sum E obtained whenthe contour model 400 is located at different positions in the secondcoordinate system with a preset distance threshold. When the sum E isless than the distance threshold, the sensing device 105 may match thesecond edge information corresponding to the contour model 400 with thefirst edge information. The sensing device 105 may record the positionX1 ^(T)=(x1,y1,z1,α1,β1,γ1) of the contour model 400 in the secondcoordinate system and stop iterating.

In some embodiments, the sensing device 105 may adjust the position ofthe contour model 400 in the second coordinate system based on Newton'smethod, to determine the second edge information that matches the firstedge information 300′. Specifically, the sensing device 105 may solve abetter position based on the following equation at each iteration:

X _(k+1) ^(T) =X _(k) ^(T)−∇² g(X _(k) ^(T))⁻¹ g(X _(k) ^(T))

Where X_(k+1) ^(T) represents a position selected in the next iteration,X_(k) ^(T) represents the current position before adjustment. Thesensing device 105 can terminate the iteration when the followingconvergence condition (i.e., the distance between adjusted adjacentpositions is less than a predetermined threshold) is satisfied:

∥X _(k+1) ^(T) −X _(k) ^(T)∥<ε

Based on the Newton's method, the sensing device 105 can determine theposition of the contour model 400 in the second coordinate system whenthe convergence condition is satisfied, for example, the position may berepresented as X1 ^(T)=(x1,y1,z1,α1,β1,γ1).

Through the above method, the sensing device 105 may determine thesecond edge from the plurality of edges indicated by the edgeinformation set, where the sum of distances between the second edge andthe plurality of points is less than the preset threshold, and selectedge information indicating the second edge from the edge informationset as the second edge information. It should be understood that, theabove method is merely illustrative, and any other suitable method maybe employed to solve for position having the minimum sum of distances.

As illustrated in FIG. 2, at block 208, the sensing device 105determines the position of the vehicle 110 relative to the sensingdevice based on the position corresponding to the second edgeinformation.

As described above, the sensing device 105 may output the position ofthe contour model 400 in the second coordinate system as the position ofthe vehicle 110 relative to the sensing device 105.

In some embodiments, after the second edge information that matches thefirst edge information 300′ is determined, the sensing device 105 candetermine the position (such as X1 ^(T)=(x1,y1,z1,α1,β1,γ1)) of thecontour model 400 corresponding to the second edge information in thesecond coordinate system. In some embodiments, the sensing device 105can derive a conversion matrix from the second coordinate system to aworld coordinate system based on its calibration information. Based onthe conversion matrix, the sensing device 105 may convert the positionof the vehicle 110 relative to the sensing device 105 (i.e., theposition X1 ^(T)=(x1,y1,z1,α1,β1,γ1) of the contour model 400 in thesecond coordinate system) to a geographic position X2^(T)=(x2,y2,z2,α2,β2,γ2) in the world coordinate system, the geographicposition may include the three-dimensional (3D) coordinate and the Eulerangle of the vehicle 110 in the world coordinate system.

Based on such a positioning manner, the sensing device not onlyconsiders the approximate area of the vehicle in the 2D image, but alsoutilizes the precise contour model of the vehicle, and projects thecontour model into the 2D image, such that the projected line matchesthe edge of the vehicle in the 2D image as much as possible, and thegeographic position of the vehicle can be determined more accurately.

In some embodiments, the sensing device 105 may transmit the geographicposition of the vehicle 110 to the vehicle 110. In some embodiments, forexample, the vehicle 110 may receive the geographic positioninformation, to fuse with the self-positioning information of thevehicle 110 to obtain a more accurate position. In some embodiments, thevehicle 110 may control the its driving based on the acquired geographicposition information.

In some embodiments, the sensing device 105 may transmit the position ofthe vehicle 110 relative to the sensing device 105 to the vehicle 110,and the vehicle 110 can determine the geographic position of the vehicle110 in the world coordinate system based on the relative positioninformation and the position of the sensing device 105.

FIG. 6 is a block diagram of a device 500 for positioning a vehicleaccording to an embodiment of the present disclosure. The device 600 maybe included in the sensing device 105 of FIG. 1 or may be realized asthe sensing device 105. As shown in FIG. 6, the device 600 includes afirst edge information determining module 602, a contour modeldetermining module 604, a second edge information determining module606, and a position determining module 608.

The first edge information determining module 602 is configured todetermine first edge information of a vehicle from an image related tothe vehicle and acquired by a sensing device. The contour modeldetermining module 604 is configured to determine a contour modelcorresponding to the vehicle. The second edge information determiningmodule 606 is configured to determine second edge information thatmatches the first edge information from an edge information setassociated with the contour model. Each edge information in the edgeinformation set corresponds to a position of the contour model relativeto the sensing device. The position determining module 608 is configuredto determine a position of the vehicle relative to the sensing devicebased on a position corresponding to the second edge information.

In some embodiments, the first edge information determining module 602may include a component configuration module, and an edge extractionmodule. The component configuration module is configured to determine atleast one component of the vehicle from the image. The edge extractionmodule is configured to extract an edge of each of the at least onecomponent.

In some embodiments, the contour model determining module 604 mayinclude an identification information determining module, and a firstcontour model determining module. The identification informationdetermining module is configured to determine identification informationof the vehicle from the image. The first contour model determiningmodule is configured to determine the contour model corresponding to thevehicle from a preset contour model set based on the identificationinformation.

In some embodiments, the identification information includesregistration plate information of the vehicle.

In some embodiments, the second edge information determining module 606includes a point determining module, a second edge determining module,and a second edge information selection module. The point determiningmodule is configured to determine a plurality of points on a first edgeindicated by the first edge information. The second edge determiningmodule is configured to determine a second edge from a plurality ofedges indicated by the edge information set. A sum of distances betweenthe second edge and the plurality of points is less than a presetthreshold. The second edge information selection module is configured toselect edge information indicating the second edge from the edgeinformation set, as the second edge information

In some embodiments, the position determining module 608 includes acoordinate and Euler angle acquiring module. The coordinate and Eulerangle acquiring module is configured to determine a coordinate and aEuler angle of the vehicle in a roadside coordinate system having thesensing device as an origin.

In some embodiments, the device 600 includes a conversion matrixacquiring module, and a geographic position conversion module. Theconversion matrix acquiring module is configured to obtain a conversionmatrix from a roadside coordinate system having the sensing device as anorigin to a world coordinate system. The geographic position conversionmodule is configured to convert the position of the vehicle relative tothe sensing device to a geographic position of the vehicle based on theconversion matrix.

In some embodiments, the device 600 further includes a transmittingmodule. The transmitting module is configured to transmit the geographicposition to the vehicle.

FIG. 7 is a block diagram of an exemplary device 700 capable ofimplementing an embodiment of the present disclosure. The device 700 maybe configured to implement the sensing device 105 of FIG. 1. As shown inFIG. 7, the device 700 includes a computing unit 701, which may beconfigured to perform various appropriate operations and processes basedon computer program instructions stored in a ROM 702 or computer programinstructions loaded from a storage unit 708 into a RAM 703. The RAM 703may store various programs and data required for operations of thedevice 700. The CPU 701, the ROM 702 and the RAM 703 may be connected toeach other through a bus 704. The input/output (I/O) interface 705 mayalso be coupled to the bus 704.

A plurality of components in the device 700 are coupled to the I/Ointerface 705, including: an input unit 706 such as a keyboard, a mouse,etc., an output unit 707 such as various types of displays, speakers,etc., a storage unit 708 such as a disk, an optical disk or the like,and a communication unit 709 such as a network card, a modem, a wirelesscommunication transceiver, or the like. The communication unit 709allows the device 700 to exchange information/data with other devicesover a computer network such as Internet and/or varioustelecommunication networks.

The computing unit 701 may include a variety of general purpose and/orspecial processing components with processing and computingcapabilities. Examples of the computing unit 701 may include, but arenot limited to, a central processing unit (CPU), a graphic processingunit (GPU), various specialized artificial intelligence (AI) computingchips, various computing units for running machine learning modelalgorithms, a digital signal processor (DSP), and any suitableprocessor, controller, microcontroller. The computing unit 701 canperform various methods and processes described above, such as themethod 200. For example, in some embodiments, the method 200 may beimplemented as a computer software program that is tangibly embodied ina machine readable medium, such as the storage unit 708. In someembodiments, some or all of the computer program may be loaded and/orinstalled on the device 700 via ROM 702 and/or the communication unit709. One or more steps of the method 200 described above may beperformed when the computer program is loaded into RAM 703 and executedby the computing unit 701. Alternatively, in other embodiments, thecomputing unit 701 may be configured to perform the method 200 by anyother suitable means (e.g., by means of firmware).

The functions described above may be performed, at least in part, by oneor more hardware logic components. For example, without any limitation,the exemplary type of the hardware logic component may include: FieldProgrammable Gate Array (FPGA), Application Specific Integrated Circuit(ASIC), Application Specific Standard Product (ASSP), System on Chip(SOC), Complex Programmable Logic Device (CPLD), etc.

The program code for implementing the method of the present disclosuremay be written in any combination of one or more programming languages.The program code may be provided to a general-purpose computer, aspecial purpose computer or a processor or controller of otherprogrammable data processing devices, such that the program code, whenexecuted by the processor or controller, causes the functions/operationsspecified in the flowcharts and/or block diagrams to be implemented. Theprogram code may be executed entirely on a machine, partially on amachine, partially on the machine as a separate package, partially on aremote machine, or entirely on a remote machine or server.

In the context of the present disclosure, a machine-readable medium maybe a tangible medium that may contain or store programs for use by or incombination with an instruction execution system, apparatus or device.The machine-readable medium may be a machine-readable signal medium or amachine-readable storage medium. The machine-readable medium mayinclude, but is not limited to, electronic, magnetic, optical,electromagnetic, infrared, or semiconductor system, apparatus or device,or any suitable combination of the above. More specific examples of themachine-readable storage medium may include electrical connections basedon one or more wires, a portable computer disk, a hard disk, a randomaccess memory (RAM), a read-only memory (ROM), an erasable programmableread-only memory (EPROM or Flash memory), an optical fiber, a compactdisk-only memory (CD-ROM), an optical storage device, a magnetic storagedevice, or any suitable combination of the above.

In addition, although the operations are depicted in a particular order,it should be understood that such operations are required to beperformed in the particular order shown or in the order, or that allillustrated operations should be performed to achieve the desiredresults. Multitasking and parallel processing may be advantageous incertain circumstances.

Likewise, although several specific implementation details are includedin the above discussion, these should not be construed as restrictionson the scope of the present disclosure. Certain features described inthe context of individual embodiments may also be implemented incombination in a single implementation. Instead, various featuresdescribed in the context of a single implementation may also beimplemented in a plurality of implementations, either individually or inany suitable sub-combination.

Although the present disclosure has been described in language specificto structural features and/or methodological acts, it is understood thatthe subject matter defined in the appended claims is not limited to thespecific features or acts described. Instead, the specific features andacts described above are merely exemplary forms of implementing theclaims.

What is claimed is:
 1. A method for positioning a vehicle, comprising:determining first edge information of a vehicle from an image related tothe vehicle and acquired by a sensing device; determining a contourmodel corresponding to the vehicle; determining second edge informationthat matches the first edge information from an edge information setassociated with the contour model, wherein each edge information in theedge information set corresponds to a position of the contour modelrelative to the sensing device; and determining a position of thevehicle relative to the sensing device based on a position correspondingto the second edge information.
 2. The method according to claim 1,wherein determining the first edge information comprises: determining atleast one component of the vehicle from the image; and extracting anedge of each of the at least one component.
 3. The method according toclaim 1, wherein determining the contour model comprises: determiningidentification information of the vehicle from the image; anddetermining the contour model corresponding to the vehicle from a presetcontour model set based on the identification information.
 4. The methodaccording to claim 3, wherein the identification information comprisesregistration plate information of the vehicle.
 5. The method accordingto claim 1, wherein determining the second edge information that matchesthe first edge information from the edge information set associated withthe contour model comprises: determining a plurality of points on afirst edge indicated by the first edge information; determining a secondedge from a plurality of edges indicated by the edge information set,wherein a sum of distances between the second edge and the plurality ofpoints is less than a preset threshold; and selecting edge informationindicating the second edge from the edge information set, as the secondedge information.
 6. The method according to claim 1, whereindetermining the position of the vehicle relative to the sensing devicecomprises: determining a coordinate and a Euler angle of the vehicle ina roadside coordinate system having the sensing device as an origin. 7.The method according to claim 1, further comprising: obtaining aconversion matrix from a roadside coordinate system having the sensingdevice as an origin to a world coordinate system; and converting theposition of the vehicle relative to the sensing device to a geographicposition of the vehicle based on the conversion matrix.
 8. The methodaccording to claim 7, further comprising: transmitting the geographicposition to the vehicle.
 9. A device for positioning a vehicle,comprising: one or more processors; and a storage device, configured tostore one or more programs, wherein when the one or more programs areexecuted by the one or more processors, causes the one or moreprocessors to: determine first edge information of a vehicle from animage related to the vehicle and acquired by a sensing device; determinea contour model corresponding to the vehicle; determine second edgeinformation that matches the first edge information from an edgeinformation set associated with the contour model, wherein each edgeinformation in the edge information set corresponds to a position of thecontour model relative to the sensing device; and determine a positionof the vehicle relative to the sensing device based on a positioncorresponding to the second edge information.
 10. The device accordingto claim 9, wherein in determining the first edge information, the oneor more processors are configured to: determine at least one componentof the vehicle from the image; and extract an edge of each of the atleast one component.
 11. The device according to claim 9, wherein indetermining the contour model, the one or more processors are configuredto: determine identification information of the vehicle from the image;and determine the contour model corresponding to the vehicle from apreset contour model set based on the identification information. 12.The device according to claim 11, wherein the identification informationcomprises registration plate information of the vehicle.
 13. The deviceaccording to claim 9, wherein in determining the second edge informationthat matches the first edge information from the edge information setassociated with the contour model, the one or more processors areconfigured to: determine a plurality of points on a first edge indicatedby the first edge information; determine a second edge from a pluralityof edges indicated by the edge information set, wherein a sum ofdistances between the second edge and the plurality of points is lessthan a preset threshold; and select edge information indicating thesecond edge from the edge information set, as the second edgeinformation.
 14. The device according to claim 9, wherein in determiningthe position of the vehicle relative to the sensing device, the one ormore processors are configured to: determine a coordinate and a Eulerangle of the vehicle in a roadside coordinate system having the sensingdevice as an origin.
 15. The device according to claim 9, wherein theone or more processors are further configured to: obtain a conversionmatrix from a roadside coordinate system having the sensing device as anorigin to a world coordinate system; and convert the position of thevehicle relative to the sensing device to a geographic position of thevehicle based on the conversion matrix.
 16. The device according toclaim 15, wherein the one or more processors are further configured to:transmit the geographic position to the vehicle.
 17. A computer readablestorage medium having stored thereon a computer program that, whenexecuted by a processor, causes a method for positioning a vehicle to beimplemented, the method comprising: determining first edge informationof a vehicle from an image related to the vehicle and acquired by asensing device; determining a contour model corresponding to thevehicle; determining second edge information that matches the first edgeinformation from an edge information set associated with the contourmodel, wherein each edge information in the edge information setcorresponds to a position of the contour model relative to the sensingdevice; and determining a position of the vehicle relative to thesensing device based on a position corresponding to the second edgeinformation.